Bridging AI and Economics
Evaluating the Feasibility of RAG Models for Regulatory Compliance
Jesús Martínez del Rincón
2024-11-20
Introduction
Collaborative Project Overview
- Led by Queen’s University Belfast researchers.
- Supported by UKRI through the UKFin+ programme.
- Aim: Evaluate the feasibility of AI (RAG models) for compliance in investment management.
Objectives
- Explore AI applications for compliance efficiency.
- Conduct economic evaluations of cost and resource use.
- Focus on reporting, risk, and monitoring improvements.
- Address challenges like adaptability and integration.
Methodology Overview
- Cost-Benefit Analysis: Evaluate direct and indirect cost impacts.
- Process Mapping: Assess workflow efficiencies.
- Simulation Modelling: Test adaptability to evolving regulations.
- Stakeholder Interviews: Capture practical insights from compliance professionals.
Preliminary Insights
- Efficiency Gains: Improved task completion times.
- Cost Reduction: Lower resource requirements for key compliance tasks.
- Stakeholder Feedback: Highlighted potential for better interpretability and usability.
Work Packages
- WP1: Define use cases and baseline metrics.
- WP2: Train RAG models for Q/A tasks.
- WP3: Automate rule extraction via OWL ontology.
- WP4: Address inconsistencies in rule sets.
- WP5: Collect qualitative insights and finalise the CBA.
Challenges and Limitations
- Data Availability: Ensuring comprehensive regulatory data.
- Model Trust: Balancing accuracy with explainability.
- Scalability: Adapting to evolving compliance requirements.
Ethical Considerations
- Fairness: Address potential biases in AI outputs.
- Transparency: Use explainable AI (XAI) methods for clarity.
- Privacy: Comply with GDPR and other data protection laws.
- Human Oversight: Support, not replace, compliance professionals.
Future Work
- Develop specialised financial language models.
- Refine retrieval mechanisms to improve accuracy.
- Study long-term economic impacts of RAG models.
- Create ethical guidelines for AI in compliance.
Thank You!
Contact Information
Dr Barry Quinn
Queen’s University Belfast
📧 barry.quinn@qub.ac.uk